Superiority of the triglyceride glucose index over the homeostasis model in predicting metabolic syndrome based on NHANES data analysis

The triglyceride-glucose (TyG) index is a simple and inexpensive new marker of insulin resistance that is being increasingly used for the clinical prediction of metabolic syndrome (MetS). Nevertheless, there are only a few comparative studies on its predictive capacity for MetS versus those using the traditional homeostasis model assessment (HOMA). We conducted a cross-sectional study using a database from the National Health and Nutrition Examination Survey (1999 March to 2020 pre-pandemic period). Using statistical methods, we compared the predictive abilities of the TyG index and HOMA (including HOMA of insulin resistance [HOMA-IR] and HOMA of beta-cell function [HOMA-β]) for MetS. A total of 34,195 participants were enrolled and divided into the MetS group (23.1%) or no MetS group (76.9%) according to the International Diabetes Federation (IDF) diagnostic criteria. After applying weighted data, the baseline characteristics of the population were described. Following the exclusion of medication influences, the final count was 31,304 participants. Receiver operating characteristic curve analysis revealed that while distinguishing between MetS and no MetS, the TyG index had an area under the curve (AUC) of 0.827 (sensitivity = 71.9%, specificity = 80.5%), and the cutoff was 8.75, slightly outperforming HOMA-IR (AUC = 0.784) and HOMA-β (AUC = 0.614) with a significance of P < 0.01. The prevalence of MetS in the total population calculated using the TyG index cutoff value was 30.9%, which was higher than that reported in the IDF diagnostic criteria. Weighted data analysis using univariate and multivariate logistic regression displayed an independent association between elevated TyG and HOMA-IR with the risk of MetS. Subgroup analysis further revealed differences in the predictive ability of the TyG index among adult populations across various genders and ethnicities, whereas such differences were not observed for children and adolescents. The TyG index is slightly better than HOMA in predicting MetS and may identify more patients with MetS; thus, its applications in a clinical setting can be appropriately increased.


Definition criteria
The following diagnostic criteria of the International Diabetes Federation (IDF) 2007 for MetS were adopted: 1. Central obesity; 2. Abnormality in any two or more of the four indicators: blood pressure, blood glucose, triglyceride, and high-density lipoprotein cholesterol.However, the criteria for adults 10 and children and adolescents 11 were different.The diagnostic criteria for adult MetS are shown in Table 1 and those for children and adolescents in Table 2.The percentage waist circumference for children and adolescents is shown in Supplementary Table S1.Questionnaire data for smoking, drinking, and education: As NHANES did not have questionnaires for smoking and alcohol consumption for children and adolescents, smoking and alcohol consumption data were collected only for individuals aged 20 years and older."Smoked at least 100 cigarettes in life" was defined as smoking, and "Had at least 12 alcohol drinks per year" was defined as drinking."Less than 9th grade" and "9th-11th grade" were defined as education below high school level; "High School Grad/GED or Equivalent" was defined as High School education level; and "Some College or AA degree" and "College Graduate or above" were defined as education above high school level.The definition of diabetes for all participants was based on the American Diabetes Association 2023 standard 12 combined with questionnaires, and if they met any of the following criteria: "Have been informed of diabetes," "Fasting blood glucose (FBG) levels ≥ 126 mg/dL" or "Glycosylated hemoglobin (HbA1c) levels ≥ 6.5%."The definition of hypertension for all participants was based on the American Heart Association/American College of Cardiology 2017 standard 13 combined with questionnaires, and if they met any of the following criteria: "Had been told about hypertension, " "Systolic blood pressure (SBP) ≥ 130 mm Hg, " or "Diastolic blood pressure (DBP) ≥ 80 mm Hg. "

Statistical analysis
R software version 4.3.1 (R Core Team, Vienna, Austria) was used for data entry and processing.Packages such as "survey, " "weights, " "matrix, " and "pROC" were mainly selected.GraphPad Prism, version 9.4.1 (GraphPad Software, San Diego, CA, USA) was used to create images.First, fasting subsample weights were selected for the weighted processing of the selected data.During the consolidation of various cycles, "4/21.2× WTSAF4YR" was chosen as the weight for the cycles from 1999-2002, whereas for the cycles from 2003 to 2016, with its 7 cycles, "2/21.2× WTSAF2YR" was assigned as the weight for each cycle.For the period from 2017 to March 2020 (pre-pandemic cycle), "3.2/21.2× WTSAFPRP" was selected as the weight.N represents the included population and WN represents the number of weighted representative American population.Continuous variable data are represented as mean ± standard error (SE), and categorical variables are represented as % (SE).T-test was used for continuous variables and Chi-square test was used for classification variables.The TyG index, HOMA-IR, and HOMA-β were transformed into dichotomous variables.After data weighting, univariate and multivariate Models 1, 2, 3, and 4 were established for logistic regression analysis.Then, the TyG index and the ability of HOMA-IR and HOMA-β to diagnose MetS were analyzed and evaluated using the receiver operating characteristic (ROC) curve, and the corresponding areas under curve (AUCs), sensitivity, and specificity were calculated.Lastly, subgroup univariate analysis was conducted for adults, children, and teenagers after data weighting based on population characteristics.As HOMA-IS is the reciprocal of HOMA-IR and its diagnostic efficiency is consistent Table 1.IDF consensus definition of metabolic syndrome in adults.IDF international diabetes federation, SBP systolic blood pressure, DBP diastolic blood pressure, FBG fasting blood glucose.
According to the adult IDF definition, for a person to be defined as having the metabolic syndrome they must have: Central obesity (defined as an raised waist circumference, in the USA it is more than 102 cm for men and more than 88 cm for women.)plus any two of the following four factors:

Ethics approval and consent to participate
The NHANES data used in this study are public data and do not contain any personally identifiable information; thus, additional ethical review was not required.We have strictly abided by NHANES data usage specifications and privacy protection policies to ensure compliance and ethical data use.

Baseline characteristics
The statistics of the data-completion ratio are shown in Table 3 www.nature.com/scientificreports/MetS group.The prevalence of MetS was 29.1% in adults and 4.8% in children and adolescents.After data were weighted for baseline analysis, the 2 groups of data were compared (Table 4).In the comparison of the TyG index and HOMA, to avoid the interference of drugs, 2,891 participants who were currently taking oral hypoglycemic and lipid-lowering drugs or using insulin were excluded.Finally, 31,304 participants were included in the analysis and were classified as 22,846 adults and 8,458 children or adolescents based on their age.Baseline analysis and intergroup comparison were conducted for each group.The baseline characteristics of adults are shown in Table 5 and those of children and adolescents in Table 6.

Predictive ability
The predictive abilities of the TyG index and HOMA for the diagnosis of MetS in the included population were further evaluated with MetS as a positive diagnosis result.ROC curves were drawn and AUCs were calculated using the TyG index, HOMA-IR, and HOMA-β.The AUC of the TyG index was 0.827 (sensitivity = 71.9%,specificity = 80.5%), and the cutoff was 8.75, which was slightly higher than that of HOMA-IR (0.784) and HOMA-β (0.614), all P < 0.01 (Fig. 2).The prevalence of MetS in the population calculated using the TyG index cutoff value was 30.9%, which was higher than that reported in the IDF diagnostic criteria (23.1%).In the adult population, the AUC of the TyG index was 0.796 (sensitivity = 69.8%,specificity = 78.5%)and the cutoff was 8.80, and the prevalence of MetS in the adult population calculated using the TyG index cutoff value was 34.1%.In the child and adolescent population, the AUC of the TyG index was 0.874 (sensitivity = 76.3%, specificity = 87.3%)and the cutoff was 8.62.The prevalence of MetS in the child and adolescent population calculated using the TyG index cutoff value was 16.4%.www.nature.com/scientificreports/

Logistic regression analysis
After the data were weighted, the TyG index, HOMA-IR, and HOMA-β were transformed into dichotomic variables as independent variables to construct Model 1. Univariate logistic regression analysis showed that high TyG index, HOMA-IR, and HOMA-β were correlated with the risk of MetS.Based on Model 1, the demographic variables (gender, age, and race) were adjusted to construct Model 2. Based on Model 2, the examined variables (body mass index, waist circumference, SBP, and DBP) were adjusted to construct Model 3. Based on Model 3, the laboratory variables (HbA1c, cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol levels) were adjusted to construct Model 4. Multivariate logistic regression analysis showed that, except for Model 4, elevated HOMA-β showed no association with the risk of MetS (odds ratio [OR] {95% confidence interval [CI]}) = 0.93 (0.80-1.07)].However, in other models, elevated TyG index, HOMA-IR, and HOMA-β were all associated with the risk of MetS, as shown in Fig. 3.

Subgroup analysis
Data were weighted for subgroup analysis and the TyG index was transformed into a binary classification variable and taken as exposure variables.Univariate analysis of the adult population revealed that the TyG index could differently predict MetS based on different genders and races (all P-interactions < 0.01).However, there was no difference in the ability of the TyG index to predict MetS among different levels of education, smoking, and drinking (all P-interactions > 0.05), as shown in Fig. 4. For the subgroup analysis of the child and adolescent population www.nature.com/scientificreports/based only on gender and race, univariate analysis revealed no differences between gender (P-interaction = 0.45) and ethnicity (P-interaction = 0.29) in the ability of the TyG index to predict MetS.

Discussion
The strength of this study is that it is the largest investigation to date that has explored the predictive ability of the TyG index and HOMA for MetS within a population sample.NHANES employs a complex, stratified, and random sampling methodology to ensure accurate and reliable test results, thereby securing data authenticity and allowing for generalization to the entire United States population.Our research findings suggest a slightly superior predictive capability of the TyG index over HOMA for MetS.
Although the hyperinsulinemic euglycemic clamp technology is currently the internationally recognized gold standard to evaluate insulin resistance, its implementation requires special equipment and skilled technicians, which is expensive and time-consuming.Moreover, multiple blood samples are required for the test, which can be difficult for patients to accept.Therefore, it is only used for scientific research and cannot be applied in clinical practice on a large scale 14 .HOMA is now commonly used to evaluate insulin function in a clinical setting.HOMA was first proposed by Turner's research team at Oxford University in 1985 9 .It is a mathematical model established to reflect the interaction of glucose and insulin in different organs (including the pancreas, liver, and surrounding tissues).The model assessed insulin resistance (HOMA-IR) and islet β-cell function (HOMA-β) only by using FBG and fasting insulin values.However, in recent years, a simpler and low-cost test method, namely the TyG index, has been widely used in clinical practice to evaluate insulin resistance.The TyG index was first proposed by scholars in South America.This index can be obtained by determining routine fasting triglyceride and FBG levels in the serum.In 2008, Simental-Mendia et al. used the TyG index for the community screening of healthy participants to check for insulin resistance 8 .Apart from reflecting insulin resistance, studies have shown that the TyG index can also be used as an indicator to predict risks of the chronic complications of diabetes 15,16 , cardiovascular disease 17 , and cerebrovascular disease 18 , among others.Meanwhile, the ability of the TyG index to evaluate MetS has attracted much attention in recent years [2][3][4] .Triglyceride levels are typically determined using enzymatic, chromatographic, or chemical methods.Among these, the enzymatic method is the most commonly used and relatively simple procedure.In our study, the triglyceride measurements extracted from the NHANES database were also analyzed using the enzymatic method.This method can be conducted relatively quickly and is suitable for handling large numbers of samples; thus, it is widely used in clinical practice.In contrast, the determination of insulin requires immunological methods such as enzyme-linked immunosorbent assay or radioimmunoassay, which involve more sample-processing steps  and experimental procedures.These methods require antibodies to bind to the substance to be measured (such as insulin), followed by the subsequent detection of the conjugated product using a marker such as an enzyme or a radioisotope 19 .Sample processing is relatively complex, especially in remote primary care facilities with limited medical resources, and insulin determination may therefore be difficult.In addition, from the point of cost-effectiveness, the TyG index only requires the detection of glucose and triglyceride concentrations, which is an inexpensive process.On the other hand, HOMA requires the detection of glucose and insulin concentrations, which are associated with higher costs 20 .Therefore, the TyG index is comparatively easier to obtain than HOMA.Moreover, HOMA-β cannot be calculated when fasting glucose levels are less than or equal to 3.5 mmol/ L. We found that the TyG index had a slightly higher AUC value compared with HOMA based on the comparison of the AUC under the ROC curve, suggesting that the TyG index has more advantages in predicting MetS.A higher AUC means that the TyG index has a better predictive ability compared with HOMA, and the sensitivity and specificity of the TyG index are also high.Therefore, these findings suggest that the TyG index may be more suitable for the early screening and prediction of MetS than HOMA, which is, therefore, worthy of further evaluation and application in a clinical setting.
At the same time, our study also found that the cutoff value of the TyG index as a predictor of MetS was 8.75 and that there was little difference in the cutoff value between the adult population and the child and adolescent population.It is noteworthy that the prevalence of MetS calculated using the TyG index cutoff values were all higher than that diagnosed using the IDF criteria across different groups, namely, the total population (30.9% vs. 23.1%),adults (34.1% vs. 29.1%),and children and adolescents (16.4% vs. 4.8%).The difference between the total population and the adult population was within 10%, suggesting that using the TyG index may identify individuals at risk for insulin resistance or early metabolic abnormalities even if they do not meet the IDF criteria.Therefore, using the TyG index may potentially identify patients with MetS at an earlier stage, providing early intervention opportunities to prevent the development of related complications.However, in the child and adolescent population, the difference in the prevalence of MetS calculated using the IDF diagnostic criteria versus the TyG index cutoff values was about 12%, a difference that could significantly increase the workload of pediatricians.This finding suggests that the TyG index may not be appropriate for identifying MetS in children and adolescents.Therefore, additional prospective longitudinal studies are needed to explore the applicability of the TyG index in this specific population.
Using univariate and multivariate logistic regression analyses, we found that high TyG index, HOMA-IR, and HOMA-β values were significantly correlated with the risk of MetS.Even after gradually adjusting for the demographic variable and examination variable and establishing multivariable Model 2 and Model 3, respectively, high TyG index, HOMA-IR, and HOMA-β values still maintained the correlation with the risk of MetS.However, when the laboratory variables were adjusted based on Model 3 and the multivariable Model 4 was established, high HOMA-β was not associated with the risk of MetS because the 95% CI was 1, likely suggesting that HOMA-β had insufficient robustness in predicting MetS.However, in Model 4, high TyG index and HOMA-IR still maintained the correlation with the risk of MetS, providing a solid foundation for the effectiveness of the TyG index and HOMA-IR in predicting MetS.
Subgroup analysis of the TyG index to predict MetS ability showed interactions between genders and races in the adult population.These findings suggested that the applicability of the TyG index in predicting MetS is influenced by different population characteristics.Our study found that the TyG index was slightly better in predicting MetS in female adults than in male adults.There are significant differences in metabolic and physiological characteristics between males and females, including lipid-metabolism patterns, fat distribution, and hormone levels.In general, sex hormone levels vary greatly between men and women, which not only affect fat distribution but also affect metabolism.Androgens are generally associated with more fat accumulation in the abdomen, whereas estrogens may influence fat accumulation in the buttocks and thighs 21 .Additionally, there are differences in basal metabolic rates between men and women, and men usually have a higher basal metabolic rate 22 .Such metabolic and physiological differences may lead to gender differences while predicting MetS.Our study found that the ability of the TyG index to predict MetS also differed among adults from different races; however, this difference was not significant.Differences in metabolic characteristics, genetics, lifestyle, and culture among ethnic groups may contribute to differences in body fat and metabolism 23 .Therefore, gender and ethnic differences in the adult population may need to be considered during the practical application of the TyG index in predicting MetS to develop more personalized prevention and intervention measures.
We acknowledge certain limitations of our study.First, due to the wide time span, variations in laboratory methods or locations for measuring glucose, insulin, and triglycerides across different cycles might have potentially influenced our results.Second, being a cross-sectional study derived from observational surveys, only associations and not causes could be established.

Conclusions
The TyG index is a convenient and easy-to-calculate parameter in clinical practice.Using NHANES data, we found that TyG still had a high diagnostic value for MetS.It even slightly outperformed the traditional HOMA and the cutoff was 8.75.The prevalence of MetS in the population calculated using the TyG index cutoff was higher than that reported in the IDF diagnostic criteria.This may help identify more cases of MetS, but as the prevalence differs widely when calculating the population of children and adolescents, the TyG index that identifies MetS may not apply to this particular population.In logistic regression analysis, after adjusting for multiple variables, the TyG index still maintained a correlation with the risk of MetS.Subgroup analysis of the adult population indicated differences in the ability of the TyG index to predict MetS in different genders and races, which may need to be considered prior to practical applications.In conclusion, the TyG index may be used to predict MetS in a clinical setting, thereby serving as an important reference for the early prevention of and intervention for MetS.The findings of our study highlight the use of this important index in future clinical practice.

Figure 4 .
Figure 4. Subgroup analysis of the TyG index in predicting MetS in the adult population.Abbreviations: TyG, triglyceride-glucose; MetS, metabolic syndrome; OR, odds ratio; CI, confidence interval.

Table 2 .
IDF consensus definition of metabolic syndrome in children and adolescents.IDF international diabetes federation, WC waist circumference, HDL-C high-density lipoprotein cholesterol, T2DM type 2 diabetes mellitus.

Table 4 .
Baseline characteristics of the general population.

Table 5 .
Baseline characteristics of the adult population after exclusion of drug interference.

Table 6 .
Baseline characteristics of children and adolescents after exclusion of drug interference.Continuous variable data are represented as mean ± SE, and categorical variables are represented as % (SE).T-test was used for continuous variables and Chi-square test was used for classification variables.MetS metabolic syndrome, WN weighted N, SE standard error, BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, HbA1c glycosylated hemoglobin, FBG fasting blood glucose, FINS fasting insulin, TG triglyceride, TC, cholesterol, HDL-C high density lipoprotein cholesterol, LDL-C low density lipoprotein cholesterol, TyG triglyceride-glucose, HOMA-IR homeostasis model assessment of insulin resistance, HOMA-IS homeostasis model assessment of insulin sensitivity, HOMA-β homeostasis model assessment of beta-cell function.